Microsatellite instability of the colorectal carcinoma can be predicted in the conventional pathologic examination. A prospective multicentric study and the statistical analysis of 615 cases consolidate our previously proposed logistic regression model

2010 ◽  
Vol 456 (5) ◽  
pp. 533-541 ◽  
Author(s):  
Ruth Román ◽  
Montse Verdú ◽  
Miquel Calvo ◽  
August Vidal ◽  
Xavier Sanjuan ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Statistical Analysis ◽  
Colorectal Carcinoma ◽  
Regression Model ◽  
Microsatellite Instability ◽  
Logistic Regression Model ◽  
Pathologic Examination ◽  
Multicentric Study

Culling in Quebec Holstein herds. 2. Study of phenotypic trends in reasons for disposal

1997 ◽  
Vol 77 (4) ◽  
pp. 601-608 ◽  
Author(s):  
J. W. Dürr ◽  
H. G. Monardes ◽  
R. I. Cue ◽  
J. C. Philpot
Keyword(s):  
Logistic Regression ◽  
Statistical Analysis ◽  
Regression Model ◽  
Logistic Regression Model ◽  
Dairy Herds ◽  
Parity Number ◽  
Increasing Trends ◽  
Agricultural Regions ◽  
Linear Contrasts ◽  
Over Time

A total of 1 558 080 lactation records from PATLQ Holstein cows were used to describe the annual trends in reasons for disposal in Quebec dairy herds from 1981 to 1994. Differences in culling trends between official and owner sampler herds, between parities, and between Quebec agricultural regions were compared. Statistical analysis was carried out by means of a logistic regression model, and the significance of trends was tested by linear contrasts. Involuntary culling had a clearly ascending trend during the period of study (from 23% in 1981 to 32% in 1994), as opposed to culling for low production (voluntary), which had a descending trend (from 16% in 1981 to 4.5% in 1994). This increase in involuntary culling was mainly due to increasing trends in culling for reproductive problems, mastitis and feet and leg problems. Official herds had a greater proportion of cows with sale codes and fewer cows culled for mastitis than owner sampler herds, and the trend for sale codes was ascending for official and stable for owner sampler herds. Culling for low production was more intensive in first parity, but all parities showed a descending trend over time. The proportion of cows with sale codes decreased with parity number. For all involuntary reasons, proportion of cows culled increased with parity number. Key words: Reasons for disposal, Holstein, Quebec, culling

Factors related to the prevalence of pathogenicYersinia enterocoliticaon pig farms

2011 ◽  
Vol 139 (12) ◽  
pp. 1919-1927 ◽  
Author(s):  
S. E. VIRTANEN ◽  
L. K. SALONEN ◽  
R. LAUKKANEN ◽  
M. HAKKINEN ◽  
H. KORKEALA
Keyword(s):  
Risk Factors ◽  
Logistic Regression ◽  
Statistical Analysis ◽  
Regression Model ◽  
Random Effects ◽  
Yersinia Enterocolitica ◽  
Logistic Regression Model ◽  
Protective Factor ◽  
Organic Production ◽  
Pig Farms

SUMMARYA survey of 788 pigs from 120 farms was conducted to determine the within-farm prevalence of pathogenicYersinia enterocoliticaand a questionnaire of management conditions was mailed to the farms afterwards. A univariate statistical analysis with carriage and shedding as outcomes was conducted with random-effects logistic regression with farm as a clustering factor. Variables with aPvalue <0·15 were included into the respective multivariate random-effects logistic regression model. The use of municipal water was discovered to be a protective factor against carriage and faecal shedding of the pathogen. Organic production and buying feed from a certain feed manufacturer were also protective against total carriage. Tonsillar carriage, a different feed manufacturer, fasting pigs before transport to the slaughterhouse, higher-level farm health classification, and snout contacts between pigs were risk factors for faecal shedding. We concluded that differences in management can explain different prevalences ofY. enterocoliticabetween farms.

scholarly journals The statistical analysis of the data of one school SEN pupils

2016 ◽  
Vol 57 ◽  
Author(s):  
Karolina Piaseckienė ◽  
Vilma Ranonienė
Keyword(s):  
Logistic Regression ◽  
Statistical Analysis ◽  
Environmental Factors ◽  
Regression Model ◽  
Logistic Regression Model ◽  
Educational Needs ◽  
Educational Process ◽  
Special Educational Needs

In the educational process, the special educational needs (for brevity, SEN) are the needs for help and services arising from children’s congenital or acquired disorders and adverse environmental factors. In this article, we analyse statistically the data of pupils with SEN. We create the logistic regression model to describe what determines the proportion of boys among all SEN pupils in certain school.

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